For the past several years I have studied how the geoweb is produced (particularly the practices surrounding user-generated data) in order to better understand where, when, and by whom geo-coded content is being created. I focus on how code, space and place interact as people increasingly use of mobile, digital technologies to navigate through their everyday, lived geographies. Of special interest is the complex and often duplicitous manner that code and content can congeal and individualize our experiences in the hybrid, digitally augmented places that cities are becoming.

As an economic geographer I also study how flows of material goods in the global economy are shaped by immaterial flows of information. Just as the global financial system is enabled by the materiality of high-speed fiber optic cables laid across the ocean, so too are the movement of cargo containers dependent upon the halo of virtual information that surrounds them as they move through space. My interest is in the range of ways in which material and virtual flows are intertwined: sometimes complementary, sometimes contradictory, but always central to the evolution of spatial relations in the economy.

The FloatingSheep research blog provide an overview of this work, particularly some of the more quirky dimensions that are hard to place in more mainstream academic outlets. After all, the Internet (and information space more generally) can be a wild and woolly place.

I am also the Director of the The DOLLY Project (Data On Local Life and You) is a repository of billions of geolocated tweets that allows for real-time research and analysis. Building on top of existing open source technology, DOLLY ingests all geotagged tweets (~8 million a day), does basic analysis, indexing and geocoding to allows real-time search throughout the entire database (3 billion tweets since Dec 2011).

DOLLY also forms the basis for establishing the Department of Geography at the University of Kentucky as a key center for critical research on big geosocial media data. We see DOLLY as both a key tool for our own work but also as a means to break down the technological barrier that is often present for researchers that would like to study big data but do not necessarily possess the required technical skills.